Carnegie School of Thought - Bounded Rationality

Discuss Herb Simon some and Organizations

When I began my PhD, I was introduced early on to a particular strain of work on management called the Carnegie School of thought. This work was primarily done in the 50s and 60s by researchers at Carnegie Institute of Technology (now called the Carnegie Mellon University). Herbert Simon and Jim March were the primary individuals involved, March continuing the work with Cyert.

Herb Simon was a very complex, analytical man. Though Simon began his life as a political scientist, publishing his dissertation in a book called Administrative Behavior, he became more interested later in artificial intelligence. My first introduction to him was in a cognitive psychology course. The instructor was describing how Simon began the first lecture of the Fall semester of one of his courses by asking his students what they accomplished. After all of the students had described their summers, Simon said that, over the summer he had designed a computer that could think like a person. It was an early version of artificial intelligence that based its decision making on the same ways in which people make decisions. Simon was an extremely influential person in computer science, artificial intelligence, cognitive psychology, and management. His influence in management, for the most part, is due to his encouragement and collaboration with James March.

The ideas within the Carnegie School are quite diverse and for this post I will focus on a concept called bounded rationality (also known as satisficing). Within Economics, it is assumed that actors make the best choice in any given decision. Satisficing, proposes that there are increased costs for some decisions or that the outcome is not as important to the actor, leading to the actor to willingly make a suboptimal choice. An example that Simon used to give was about lunch [I have modified the story from the original but the idea is the same]. If an actor is in their office and needs to get lunch, they could have multiple values that they desire to maximize: timeliness, cost, health, etc. An actor could determine the relative weight of those characteristics and make the optimal choice. But as Herb said "I would instead just always go to [the student center]. For those who have been there, it is obviously a non-optimal choice." The humorous example does have certain limitations but provides a good overall example of the concept. Satisficing proposes that the act of making a choice is costly and ones own desires are not always clear, leading to a "good enough" choice being much easier to determine than the best.

Though this concept, while somewhat of a refinement of the economic theory of optimization, was a revelation to the academic world. It is not without its detractors. A comment that I have heard from several proponents of bounded rationality is that it is not testable meaning it is not a proper theory. The reason for this is that people may actually be making optimal choices but they are optimizing on unknown or unmeasured criteria. I personally think that satisficing is a very useful concept though it does have a subcurrent of nondeterminism that also arises in March's concept of the Garbage Can Model of Organizational Choice. This concept is a bit unsettling, but still interesting to me.

Comments on Data Analysis and Statistics

Analyzing data is quite an odd experience in the research world. In statistics classes, you learn about a lot of complicated models, tests, and assumptions. But, my experience analyzing data from experiments is that much of what is learned in the classroom is ignored. That isn't to say that I willingly defy the instruction I received in my classes. Instead it is that the things I learned in the majority of my stats classes are not that important for studying experiments.

Why is there this disconnect? First, most experiments are technically immune from a lot of the potential problems that stats classes teach you about. If there is random assignment to condition then individual differences shouldn't matter. Manipulations and some dependent measures can be thought of as perfect measures because they are the thing itself. I don't have a huge amount of experience in this area but the data I have typically gotten from experiments does not typically violate assumptions or is unable to violate the assumptions on ANOVA or regression such as independence. A social psychologist once implied to me that, in our field, if you use fancy statistical techniques or describe all of the tests for assumptions that you ran on the data that it can make any effects less believable. The researcher proposed this because most of the effects we investigate are measurable by ANOVA or linear regression. The researcher may be using fancy statistics because that is the only occasion when the effect exists.

This is an interesting situation because, if this is really the case, it suggests that at least part of social psychology is unwilling to accept advances in statistical procedures or statistical rigor because they don't want to be seen as hiding behind the math. If a paper doesn't use one of a small handful of methods then they are open to criticism for their statistical methods. If they use simple analyses, however, they are less open to complaints about their statistics. This may not be the true case or the case in the majority of social psychology, but I have reason to believe that it exists. It is also certainly true that a sign of experimenter 'p-hacking' is the use of convoluted analyses that may not be entirely appropriate, leading to spurious effects.

I don't mean to suggest that new innovations never make it into social psychological research. Preacher and Hayes have made a huge splash in the psychological community by introducing a way to more accurately gauge the existence and the effect size for many kinds of statistical mediations. I think that a partial reason for this acceptance, however, was their demonstration that the traditional ways of testing for mediations were more likely than their method to say that there is no mediation when a mediation does actually exist. This fact made the acceptance of a new method more appealing to the community at large, partially because it is more accurate and especially because it is more accurate in such a direction that mediations that were previously not supported may now be supported.

It is an interesting world that I honestly do not know much about. As far as journal publications go, if the editor and reviewers (normally no more than 5 people in total) think the stats you use are okay then your work can be published. If the stats are easier to understand, then your work is more likely to be published. Also, if your stats are very hard to understand because the methods are very obscure or new can also lead to your work being published. Though there were multiple issues with Daryl Bem's 2011 paper in JPSP (a very prestigious journal), but one criticism was that the stats he used were too complex and picked up on subtle, random differences. I think that the analytical world I live in is very interesting, but I just don't understand it sometimes.

Turnover and enactment of change

In much of the literature about turnover, it is unclear how newcomers are influencing the outcomes for the groups that they join. More recent literature has attempted to categorize the ways that newcomers adapt to the groups they join and how groups adapt to the newcomers. In the study I describe today, the researchers were curious what factors influence whether a newcomer is able or willing to share their ideas with the rest of the group. There is an assumption in much of the management literature that newcomer's primary value is in the new ideas they bring to the group. But, under what conditions that occurs is less clear. It certainly is not as often as possible or there would be much more value in the world.

The study I want to describe is Kane, Argote, & Levine (2005). These researchers decided to use an experiment to investigate some of their ideas using the frame of social identification. The researchers proposed that if group member shared a common social identity with a newcomer that they would be more willing to accept new ideas into the group. Unfortunately, this study was not able to determine directionality (whether the effect is newcomers' willingness to give ideas or oldtimers' willingness to accept them) but this step was a great step forward in this research.

In this task, the participants made paper boats in assembly lines. The researchers demonstrated how paper boats could be made but were clear that their requirement was to make as many paper boats that fit the requirements for the task and not just this specific boat. Some groups learned a method of making paper boats that required 7 folds while other groups learned a method that took 12 folds. Though the group with the smaller number of folds had one fold that was somewhat complex, they were much more efficient in general than groups with 12 folds (based on pretesting). The groups were told to use an assembly line to construct the boats and the more difficult fold is done by the middle member.

The other manipulation in the study was whether the groups shared a sense of collective social identity with each other. In each experimental session, 2 groups were brought into the lab at the same time. They both also participated in a training period in the same room. However, in the high social identity condition, the groups were given the same names, seated in an integrated fashion differently, and given a reward scheme where the performance of both groups would lead to better outcomes for all the individuals. In the low social identity condition, these three factors were changed so the groups seemed less similar to one another and their reward was not interdependent with the other team.

The other action in the study that the experimenters made was very clever. The middle members for each group switched from participating with one group to participating in another group. Therefore, for some groups the new member had the same experience as the group they are entering (experience with low or high efficiency folding techniques) whereas for other groups there was a difference (the new member has the low or high efficiency folding technique but the group they join has the opposite). The new member is therefore in a position where they need to learn the technique the group is using, or the member needs to try and get the group to accept the way of doing the task that they are most used to.

Skipping ahead to the results, almost no groups accepted the newcomers folding strategy if the strategy was worse than the one that they already have. There was also a main effect of the identity. Shen the groups had a shared identity, they were much more likely to accept the new member's strategy into their group. If the groups shared an identity (from having the same group name and having a shared reward structure, then they accepted the new member's better way of constructing the boat about 70% of the time. If they didn't share that same identity, however, then the group didn't accept the new member's superior way of making the boat that often (only 25% of the time).

The results for performance were a bit harder to interpret. All groups performed better over time, generating more boats in the last trial than in the first one. But there wasn't a strong direct relationship of the new member having a superior routine and performance. The researchers found that when the new member introduced a better routine to the group, that they experienced a larger increase in their performance than when the new member has a worse routine. These differences, however, are only for groups that share an identity with the new member. If the group didn't share an identity with the new member, then it didn't matter whether the new member had a better or worse routine, partially because these groups accepted that routine infrequently.

In context, this study was very significant for a few reasons. First, Argote had done significant work on learning within groups and organizations. This, however, was one of the first study that demonstrates both how learning can occur within a group and that there are certain variables that influence whether a group can learn from a new member. The variable of interet here was social identity but other work has looked at a lot of other factors (see Rink et al., 2013 or a review). Second, this study demonstrated that groups have the ability to recognize advantageous strategies and use them. This was demonstrated in some earlier work by McGrath, but Kane's study is a very clean experimental setting. Lastly, the results suggest that learning new strategies can be costly to a group, hence the small differences in performance for groups where the new member had a better routine compared to groups that received a new member with a less efficient routine.